Optimization of Metascheduler for Cloud Machine Learning Services
Author:
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Computer Science Applications
Link
https://link.springer.com/content/pdf/10.1007/s11277-020-07367-2.pdf
Reference30 articles.
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3. Nesmachnow, S., Iturriaga, S., & Dorronsoro, B. (2015). Efficient heuristics for profit optimization of virtual cloud brokers. IEEE Computational Intelligence Magazine, 10(1), 33–43.
4. Kim, S. H., Kang, D. K., Kim, W. J., Chen, M., & Youn, C. H. (2016). A science gateway cloud with cost-adaptive VM management for computational science and applications. IEEE Systems Journal, 11(1), 173–185.
5. Karthick, A. V., Ramaraj, E., & Kannan, R. (2013, December). An efficient Tri Queue job Scheduling using dynamic quantum time for cloud environment. In 2013 International Conference on Green Computing, Communication and Conservation of Energy (ICGCE) (pp. 871–876). IEEE.
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